iQSPR in XenonPy: A Bayesian Molecular Design Algorithm

iQSPR in XenonPy: A Bayesian Molecular Design Algorithm
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DOI:
10.1002/minf.201900107
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发表时间:
2019-11
影响因子:
3.6
通讯作者:
Stephen Wu;G. Lambard;Chang Liu;H. Yamada;Ryo Yoshida
Stephen Wu;G. Lambard;Chang Liu;H. Yamada;Ryo Yoshida
中科院分区:
医学4区
文献类型:
--
作者:
Stephen Wu;G. Lambard;Chang Liu;H. Yamada;Ryo Yoshida

文献摘要

相似文献

iQSPR 是我们之前的研究中开发的基于贝叶斯推理的逆分子设计算法。在这里,该算法作为一个名为 iQSPR-X 的新模块集成在 Python 中,集成在一体化材料信息学平台 XenonPy 中。我们的新软件提供了一个灵活、易于使用且可扩展的平台,供用户使用 XenonPy 中的预设模块和预训练模型库构建定制的分子设计算法。在本文中,我们描述了 iQSPR-X 的主要特征并提供了其使用指南,并通过针对特定带隙和介电常数范围的聚合物设计的应用进行了说明。
iQSPR is an inverse molecular design algorithm based on Bayesian inference that was developed in our previous study. Here, the algorithm is integrated in Python as a new module called iQSPR‐X in the all‐in‐one materials informatics platform XenonPy. Our new software provides a flexible, easy‐to‐use, and extensible platform for users to build customized molecular design algorithms using pre‐set modules and a pre‐trained model library in XenonPy. In this paper, we describe key features of iQSPR‐X and provide guidance on its use, illustrated by an application to a polymer design that targets a specific range of bandgap and dielectric constant.